Top Senior Data Engineer Jobs in Atlanta, GA

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Build and maintain scalable batch, streaming, and real-time data pipelines, platforms, data lakes, warehouses, and lakehouses. Implement data quality, governance, security, observability, automation, and cloud modernization. Partner with product, engineering, analytics, data science, and business teams to deliver analytics, AI/ML, reporting, and customer insight solutions. Troubleshoot production issues, guide architecture, mentor engineers, and provide technical leadership across marketing data initiatives.

Designs and maintains enterprise data architecture, pipelines, ETL/ELT workflows, and financial data integrations using Snowflake, AWS, dbt, Informatica, and relational databases. Ensures data quality, develops reporting and dashboards, supports financial planning and analysis, and delivers technology projects end to end. Partners with Finance, Accounting, FP&A, and technology teams, contributes to Agile planning, mentors junior staff, applies AI-assisted tools, and improves data processes and analytical capabilities.

Build, deploy, and operationalize complex data pipelines and solutions using Databricks, cloud platforms, Python, and SQL. Responsibilities include data transformation, cleansing, governance, security, quality, source analysis, testing, defect resolution, and support for AI, machine learning, and business intelligence. The role also involves cross-team collaboration, stakeholder education, and delivery of resilient data products.

Architects and implements scalable data pipelines and enterprise data solutions spanning data lakes, warehouses, marts, and distributed systems. Designs dimensional and semantic data models, curated datasets, and Power BI reporting solutions with DAX, security, governance, and performance optimization. Establishes data lineage, metadata, stewardship, compliance, and secure access practices. Collaborates with stakeholders to translate business and reporting requirements into reusable analytics assets, while supporting AI and MLOps data pipelines across cloud and hybrid platforms.

Design and maintain scalable cloud data pipelines, ELT/ETL workflows, ingestion frameworks, and data models supporting cloud cost visibility and optimization. Use Python, SQL, dbt, Airflow, AWS services, and Snowflake to deliver reliable, auditable, cost-efficient data systems. Partner with Engineering and Finance stakeholders, optimize performance, ensure data quality, and support usage-based decision-making.

Design, build, and optimize scalable ELT pipelines into BigQuery, create dbt models and data models, implement data quality, observability, CI/CD, and IaC practices, and partner with stakeholders to deliver trusted enterprise data products.

Build and evolve enterprise Master Data Management capabilities using Reltio, creating trusted customer and merchant golden records. Drive data quality, identity resolution, matching, survivorship, validation, enrichment, stewardship, integrations, and scalable data pipelines. Collaborate with architects, product owners, governance teams, and business stakeholders to translate requirements into technical solutions, optimize platform performance, and improve data accuracy, governance, compliance, and operational effectiveness.

Design, build, and optimize modern Azure and Databricks data platforms for clients. Develop batch and streaming ingestion pipelines, lakehouse and medallion architectures, dimensional models, and transformation workflows. Lead discovery sessions, requirements workshops, architecture discussions, and solution reviews. Recommend practices for governance, lineage, monitoring, DevOps, security, and data modeling while translating business needs into scalable technical solutions and communicating with technical and executive stakeholders.

Build, optimize, and maintain data pipelines, ETL processes, data architectures, AI solutions, and analytics platforms. Develop cloud-based solutions using Azure Functions and containerization, implement CI/CD workflows, integrate databases and APIs, and ensure data quality, monitoring, reliability, and documentation. Troubleshoot production issues, collaborate with cross-functional teams, and apply modern data engineering, AI, cloud, and DevOps practices.

Design, build, optimize, and maintain scalable batch and near-real-time data pipelines across on-premises and cloud platforms. Develop Snowflake data models, manage enterprise data integration and governance, implement data quality controls, and support reporting and analytics. Collaborate with data scientists, analysts, infrastructure, DevOps, privacy, and compliance teams. Troubleshoot pipeline issues, monitor performance, participate in architecture and Agile development activities, and mentor associate data engineers.

Lead design, build, and maintain scalable data pipelines, ETL processes, data models, and storage solutions. Support production data ecosystem, optimize performance, ensure data quality and security, integrate data sources/APIs, and provide technical guidance to teams while collaborating with stakeholders.

Designs and maintains scalable data pipelines, ETL jobs, data lake integrations, CI/CD workflows, Snowflake solutions, governance controls, and data quality monitoring. Develops automated transformations, incremental loads, CDC processes, testing strategies, and database workflows using Talend, Python, SQL, and cloud technologies. The role also includes mentoring engineers, conducting code reviews, optimizing performance and costs, and maintaining compliance and lineage across enterprise data systems.

Designs and maintains scalable financial data pipelines, ETL/ELT workflows, data models, quality frameworks, and enterprise application integrations. Develops dashboards and reporting with BI tools, supports financial planning and forecasting, and delivers data-driven solutions in partnership with Finance, Accounting, and FP&A. Leads small to medium projects, contributes to larger programs, mentors junior engineers, participates in Agile planning, evaluates emerging AI and data technologies, and improves processes, accuracy, and automation.

Leads the architecture, development, and operation of scalable enterprise data platforms, pipelines, ETL/ELT workflows, and transactional lakehouses. Uses AWS Glue, Apache Spark, Apache Hudi, and Amazon Athena to deliver production-grade data solutions. Provides data architecture leadership, code reviews, technical standards, query optimization, CI/CD integration, troubleshooting, and mentoring while collaborating with clients, product managers, and cross-functional teams.

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

Design, build, and maintain enterprise analytics solutions, semantic models, and reporting datasets using Microsoft Fabric, Databricks, SQL, Python, and BI tools. Lead data modeling, data quality, CI/CD, and performance optimization; translate business requirements into scalable analytics; mentor engineers and collaborate with architects and stakeholders to deliver trusted, self-service and executive reporting across the Americas.

Designs, builds, and maintains scalable data infrastructure, streaming and batch pipelines, and data products. Works with stakeholders to model, transform, and deploy data solutions using cloud, streaming, and ETL frameworks while ensuring governance, observability, and automated CI/CD deployments.

Design, develop, and maintain enterprise data solutions and pipelines using Azure data platform and Microsoft Fabric. Support data modeling, master data management, medallion architecture, data quality, and integrations to produce trusted, scalable data for analytics and BI.

Build, operate, and monitor ETL/ELT pipelines between marketing, sales, and operational systems into Databricks. Implement dimensional models, identity resolution, data quality checks, API integrations, and scheduled/event-driven syncs to support segmentation, attribution, and campaign activation. Maintain documentation, alerting, and runbooks.

Design, build, and operationalize complex data pipelines and products to support analytics and AI/ML. Analyze and transform source data, enforce data governance/security/quality, resolve high-complexity incidents, mentor team members, and partner with business stakeholders to deliver reusable, scalable data platform capabilities.

Leads data engineering for Payment Operations monitoring transformation. Designs and maintains Snowflake pipelines, tables, stored procedures, monitoring scenarios, KPI infrastructure, and data quality controls. Serves as the Snowflake subject matter expert, documents architecture and operational processes, guides technical partners, and translates business needs into scalable data solutions. The role requires production data engineering experience, advanced SQL, Snowflake expertise, job scheduling, pipeline operations, and stakeholder communication.

Lead design and delivery of the enterprise Data Platform including data lake, analytics, and certified data products. Architect solutions, automate pipelines, implement monitoring, mentor engineers, translate business needs into technical architectures, and document systems for sustainability.

Design and build cloud-native, scalable data solutions for systematic trading. Partner with traders, quants, and architects to develop Snowflake-based ETL, data models, and pipelines; lead AI-driven capability adoption; ensure security and SDLC best practices.

The Senior Data Engineer at BeyondTrust designs and manages data infrastructure, creates ETL pipelines, and optimizes database performance while ensuring data governance.